Electronic maps become increasingly popular with the development of science and technology. On one hand, people can navigate by using electronic maps to facilitate the traveling. One the other hand, with the rise of driverless vehicles, the driverless vehicles can recognize surrounding environment by using electronic maps, thereby controlling behaviours of the driverless vehicles, such as steering, acceleration or deceleration.
With regard to the existing electronic map data, a raw map is usually obtained by satellite surveying and mapping, and the navigation map information is manually and periodically updated. Following problems exist. The precision is low, and errors are generally in the range of meters or even tens of meters. Dimensionality of the data is insufficient. For example, information in various dimensions such as road lane marking information, height information, road shape information, road slope information, road curvature information, road direction information, lane width information, crash barrier information, or road border information, is absent. Data generating efficiency is low and a lot of manual operations are needed.